CSc 630

Emphasis will be placed on the interaction of image data with computer vision
and machine learning. Thus this course will have a significant computer vision
component, and should be considered by anyone interested in computer vision,
machine learning, or artificial intelligence in general. Those interested in
databases and human computer interfaces may also wish to consider this course.

Description

Large multimedia data sets are becoming increasingly available, and they
offer great opportunity, but our ability to exploit them is minimal. This
course will focus on current approaches for searching, browsing, and mining
various types of data such as text, web links, images, sound, video, and
scientific collections. The focus will be on applying methods from machine
learning and computer vision to these problems. In addition, computer
vision will be studied as a data mining problem.

Pre requisite

None other than the normal qualifications required to take graduate level
computer science courses. However, note that some of the material is quite
mathematical, and students should be prepared to struggle with it. More
specifically, a side affect of this course is that a number of generally
useful mathematical methods will be learnt/reviewed including:

This course is research focused. Students will be expected to read a number
of current papers, present and lead the discussion for several of them, and
do a project. Research oriented projects will be strongly encouraged. Due
to the inter-disciplinary nature of the course there should be plenty of
scope to integrate projects with any of a number of research projects.
Specifically projects emphasizing computer vision, machine learning,
databases, and human computer interaction are all possible. Group projects
will be encouraged. A short presentation of each project will be required.

Before the day when specific papers will be presented,
students should E-mail the instructor a short message containing feedback
on the reading material. These can be summaries, comments, notes, questions
for discussion, etc. Any format which helps you to think about the material
is acceptable. (For some background material, answers to a few questions
may be required instead).

Each student will take the class for one lecture. The reading for that
session should be presented with material from other sources as necessary.
For example, if your paper is on some standard mathematical method. it would
be of interest to do a quick survey of any on-line code that is available on
the web. Within a few days of the presentation, the presenter should E-mail
the instructor PDF slides for the session. The presenter should try to keep
the sessions interactive, and leave plenty of time for group discussion
(which is lead by the presenter). Thus the formal presentation need not
exceed 40 minutes. If we decide as a class that it is easiest to cooperate
on the printing of materials, then it will be up to the proposed presenter
to distribute those materials at least one week in advance.

Students will be expected to participate in the course in a number of other
ways. By their nature the following activities are not required from every
student for every meeting.

Any comments/suggestions that you have on your peers' presentations should
E-mailed to the instructor. I will distill and extend them, and pass them
onto the appropriate parties.

Participation in class discussion will be expected.

Any other activities that help the aims of this class and/or the research
done as part of your peers' projects can count towards participation. An
example might be filling out a web survey which collects data on how well
results fulfill queries.

Project Milestones

February 21: By this date you should have either proposed a project OR contacted
me to discuss some of the options that may suit you.

March 17: By this date you should have proposed a project.

You are strongly encouraged to do a project which is useful to someone's
research program--preferably your own! If you are actively doing research (say
as part of a PhD or Master's thesis), you should be thinking of how some of the
ideas and techniques that we have been discussing might apply to it. I will
also be providing a number of project possibilities which may be of interest.

Class Schedule

On Jan 15 there will be an introductory meeting led by the instructor. For most
subsequent meetings the class will be led by the presenter for that day.
Students should sign up to lead the discussion for one of the days as soon as
possible. If you need to change later, then arrange a swap with someone, and
let the instructor know.

Depending on
the number of students presentating, some of the slots may be taken up by the
instructor, guest lecturers, or project presentations. The list of papers will
be under construction for much of the term, and may be modified to suit student
interest or other reasons. However, every reasonable attempt will be made to
restrict changes to slots at least two weeks in the future.

A few papers are not available on-line. They will be made available
in class by the instructor. Extra copies will be put
outside the instructor's office.

Note that a few of these links will only work from UA CS machines, as these
papers are not available to the general public. (A few are semi-priveleged
documents, and the others are available to the UA community through the UA
library subscription to on-line journals. Most journal articles of interest to
us are available in this way. If you are not already familiar with this service,
I suggest that you start taking advantage of it.)

Search the audio, browse the video--a generic paradigm for video collections
(Amir et al.) [ I don't know of an electronic source, copies will provided in
class and extra ones will be available outside my office. ]

Apr 28

GROUP

An introduction to hidden Markov models
(/ and Juang) [ I don't know of an electronic source, copies will provided in
class and extra ones will be available outside my office. ]